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@Prottoy2938
Created March 18, 2020 10:02
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Dijkstra's algorithm implementation in JavaScript
//Dijkstra algorithm is used to find the shortest distance between two nodes inside a valid weighted graph. Often used in Google Maps, Network Router etc.
//helper class for PriorityQueue
class Node {
constructor(val, priority) {
this.val = val;
this.priority = priority;
}
}
class PriorityQueue {
constructor() {
this.values = [];
}
enqueue(val, priority) {
let newNode = new Node(val, priority);
this.values.push(newNode);
this.bubbleUp();
}
bubbleUp() {
let idx = this.values.length - 1;
const element = this.values[idx];
while (idx > 0) {
let parentIdx = Math.floor((idx - 1) / 2);
let parent = this.values[parentIdx];
if (element.priority >= parent.priority) break;
this.values[parentIdx] = element;
this.values[idx] = parent;
idx = parentIdx;
}
}
dequeue() {
const min = this.values[0];
const end = this.values.pop();
if (this.values.length > 0) {
this.values[0] = end;
this.sinkDown();
}
return min;
}
sinkDown() {
let idx = 0;
const length = this.values.length;
const element = this.values[0];
while (true) {
let leftChildIdx = 2 * idx + 1;
let rightChildIdx = 2 * idx + 2;
let leftChild, rightChild;
let swap = null;
if (leftChildIdx < length) {
leftChild = this.values[leftChildIdx];
if (leftChild.priority < element.priority) {
swap = leftChildIdx;
}
}
if (rightChildIdx < length) {
rightChild = this.values[rightChildIdx];
if (
(swap === null && rightChild.priority < element.priority) ||
(swap !== null && rightChild.priority < leftChild.priority)
) {
swap = rightChildIdx;
}
}
if (swap === null) break;
this.values[idx] = this.values[swap];
this.values[swap] = element;
idx = swap;
}
}
}
//Dijkstra's algorithm only works on a weighted graph.
class WeightedGraph {
constructor() {
this.adjacencyList = {};
}
addVertex(vertex) {
if (!this.adjacencyList[vertex]) this.adjacencyList[vertex] = [];
}
addEdge(vertex1, vertex2, weight) {
this.adjacencyList[vertex1].push({ node: vertex2, weight });
this.adjacencyList[vertex2].push({ node: vertex1, weight });
}
Dijkstra(start, finish) {
const nodes = new PriorityQueue();
const distances = {};
const previous = {};
let path = []; //to return at end
let smallest;
//build up initial state
for (let vertex in this.adjacencyList) {
if (vertex === start) {
distances[vertex] = 0;
nodes.enqueue(vertex, 0);
} else {
distances[vertex] = Infinity;
nodes.enqueue(vertex, Infinity);
}
previous[vertex] = null;
}
// as long as there is something to visit
while (nodes.values.length) {
smallest = nodes.dequeue().val;
if (smallest === finish) {
//WE ARE DONE
//BUILD UP PATH TO RETURN AT END
while (previous[smallest]) {
path.push(smallest);
smallest = previous[smallest];
}
break;
}
if (smallest || distances[smallest] !== Infinity) {
for (let neighbor in this.adjacencyList[smallest]) {
//find neighboring node
let nextNode = this.adjacencyList[smallest][neighbor];
//calculate new distance to neighboring node
let candidate = distances[smallest] + nextNode.weight;
let nextNeighbor = nextNode.node;
if (candidate < distances[nextNeighbor]) {
//updating new smallest distance to neighbor
distances[nextNeighbor] = candidate;
//updating previous - How we got to neighbor
previous[nextNeighbor] = smallest;
//enqueue in priority queue with new priority
nodes.enqueue(nextNeighbor, candidate);
}
}
}
}
return path.concat(smallest).reverse();
}
}
//EXAMPLES=====================================================================
var graph = new WeightedGraph();
graph.addVertex("A");
graph.addVertex("B");
graph.addVertex("C");
graph.addVertex("D");
graph.addVertex("E");
graph.addVertex("F");
graph.addEdge("A", "B", 4);
graph.addEdge("A", "C", 2);
graph.addEdge("B", "E", 3);
graph.addEdge("C", "D", 2);
graph.addEdge("C", "F", 4);
graph.addEdge("D", "E", 3);
graph.addEdge("D", "F", 1);
graph.addEdge("E", "F", 1);
console.log(graph.Dijkstra("A", "E"));
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